Systems | Development | Analytics | API | Testing

One of the most powerful capabilities provided by Kong Konnect Enterprise is the support for Hybrid deployments. In other words, it implements distributed API Gateway Clusters with multiple instances running on several environments at the same time. Moreover, Kong Enterprise provides a new topology option, named Hybrid Mode, with a total separation of the Control Plane (CP) and Data Plane (DP).

This post tells a story of a performance mistake that is quickly made even by experienced developers: The expectation that a built-in PHP function has better performance than a better suited data structure written in PHP. The protagonist in these stories is array_unique, a function that takes a list of values and removes duplicate entries to return a list of each value occurring only once.

While Kubernetes is a very powerful and comprehensive application, it can also be very complicated and confusing to new users. Thankfully, the community is great at pulling together to try to tame the Kubernetes beasts, and as more users join the platform, more handy tools to help you manage your cluster are developed. Kubernetes Resources range from everyday helper tools to development tools to troubleshooting tools, and in this article we’ll discuss fifteen of the best ones.

Many of you rely on Dataflow to build and operate mission critical streaming analytics pipelines. A key goal for us, the Dataflow team, is to make the technology work for users rather than the other way around. Autotuning, as a fundamental value proposition Dataflow offers, is a key part of making that goal a reality - it helps you focus on your use cases by eliminating the cost and burden of having to constantly tune and re-tune your applications as circumstances change.

Businesses of all sizes and entire industries rely on analyzing personal data to beat their competitors and better serve their customers. For example, information from your CRM (customer relationship management) software can help you understand how to convert more leads in a particular area or from a specific demographic.

When you secure a new data engineering position, it’s important to get off on the right foot. You need to respond to new data sources, data types, data sets, and applications efficiently. In the era of Big Data, this can be more than challenging. During this early stage of your job transition, you need to impress, and you can do this by re-thinking your data engineering strategy.

Whether you’ve made your first steps toward digital transformation or looking for ways to expand on the your current tech stack, you probably have at least one API in use. You know by now that APIs are more than pieces of code: they are products that can expand your business opportunities. They can facilitate your business’ growth with new capabilities and new revenue streams. But building and deploying APIs is only the beginning of the API lifecycle.

If you’re planning to upgrade your business technology, this almost certainly means working with an API. Either you’re building your own to integrate your on-premises technology, importing a third-party API for added functionalities, or monetizing your current capabilities. Regardless, you may find yourself working with a lot of APIs in the near future. But you may not know what to look for in searching for a high-quality API.

DreamFactory specialises in REST API generation for any number of database types however an underrepresented benefit is the ability to mount and manage any third party API via a HTTP service connector such as a Typeform REST API. This gives you the ability to generate documentation and secure an existing API as if it were created natively within DreamFactory.

Since the release of Cloudera Data Visualization (DV) back in Oct 2020, our primary mission has been to expand access to data analytics and predictive insights across enterprise businesses.